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【免费开源】AI语音合成工具——效果堪比真人 |
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  <h1 itemprop="name headline">【免费开源】AI语音合成工具——效果堪比真人
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    <p>对于一个医学生来说，经常访问 github 能帮助他开阔计算机视野。前几天在 github 找到了一个<span class="exturl" data-url="aHR0cHM6Ly9naXRodWIuY29tL1JWQy1Cb3NzL0dQVC1Tb1ZJVFMv"> AI 语音合成项目</span>，截止目前已经有了 7.7kstar, 后来知道是 b 站 up 主 “花儿不哭” 大佬和他的团队做的开源免费项目，并在 b 站发了专门的<span class="exturl" data-url="aHR0cHM6Ly93d3cuYmlsaWJpbGkuY29tL3ZpZGVvL0JWMTJnNHkxbTdVdy8/c3BtX2lkX2Zyb209MzMzLjMzNy5zZWFyY2gtY2FyZC5hbGwuY2xpY2s=">视频</span>。up 讲的比较快我最先也没看懂，推荐看<span class="exturl" data-url="aHR0cHM6Ly93d3cuYmlsaWJpbGkuY29tL3ZpZGVvL0JWMVA1NDExMTd5bi8/c3BtX2lkX2Zyb209MzMzLjMzNy5zZWFyY2gtY2FyZC5hbGwuY2xpY2s=">这个视频</span>。</p>
<p>这门技术制作出的语音，效果堪比真人，有<span class="exturl" data-url="aHR0cHM6Ly93d3cuYmlsaWJpbGkuY29tL3ZpZGVvL0JWMTNONDExSjdnTS8/c3BtX2lkX2Zyb209MzMzLjk5OS4wLjA="> AI 毕导解说红警的</span>、有<span class="exturl" data-url="aHR0cHM6Ly93d3cuYmlsaWJpbGkuY29tL3ZpZGVvL0JWMWFRNHkxdzdiRi8/c3BtX2lkX2Zyb209MzMzLjMzNy5zZWFyY2gtY2FyZC5hbGwuY2xpY2s="> AI 东雪莲的</span>，我用来做<span class="exturl" data-url="aHR0cHM6Ly93d3cuYmlsaWJpbGkuY29tL3ZpZGVvL0JWMURCNDIxNjdNSi8/c3BtX2lkX2Zyb209MzMzLjk5OS4wLjA="> gal 杂谈视频</span>。效果堪比真人，隔壁毕导的话：我真以为是我在解说！！！我心想我什么时候解说过！！！</p>
<hr>
<p>先放一键整合包链接：<br>
<span class="exturl" data-url="aHR0cHM6Ly9wYW4uYmFpZHUuY29tL3MvMU9FNXFMMEtyZU8tQVNId202Wmw5Z0E/cHdkPW1xcGklRUYlQkMlODglRTUlQkElQTYlRTclOUIlOTglRTglQTYlODElRTYlQjAlQUElRTglQjYlODUlRTclQkElQTclRTQlQkMlOUElRTUlOTElOTglRTYlODklOEQlRTglODMlQkQlRTYlQkIlQTElRTklODAlOUYlRTQlQjglOEIlRTglQkQlQkQlRUYlQkMlODk=">https://pan.baidu.com/s/1OE5qL0KreO-ASHwm6Zl9gA?pwd=mqpi（度盘要氪超级会员才能满速下载）</span><br>
<span class="exturl" data-url="aHR0cHM6Ly93d3cuMTIzcGFuLmNvbS9zLzV0SXFWdi1HVlJjdi5odG1sJUVGJUJDJTg4JUU1JThGJUFGJUU2JUJCJUExJUU5JTgwJTlGJUU0JUI4JThCJUU4JUJEJUJEJUU0JUJEJTg2JUU2JTk4JUFGJUU4JUE2JTgxJUU2JUIzJUE4JUU1JTg2JThDJUU4JUI0JUE2JUU1JThGJUI3JUVGJUJDJTg5JUVGJUJDJThDJUU2JThFJUE1JUU0JUI4JThCJUU2JTlEJUE1JUU1JTg2JTk5JUU0JUI4JTgwJUU1JTg2JTk5JUU0JUJEJUJGJUU3JTk0JUE4JUU2JTk2JUI5JUU2JUIzJTk1JUUzJTgwJTgy">https://www.123pan.com/s/5tIqVv-GVRcv.html（可满速下载但是要注册账号），接下来写一写使用方法。</span></p>
<hr>
<p>分以下情况：</p>
<h1>我是小白，我的电脑显卡配置很好，我用的windows系统</h1>
直接下载楼上的一键整合包，按[视频](https://www.bilibili.com/video/BV1P541117yn/?spm_id_from=333.337.search-card.all.click)讲解操作。值得注意的是，在人声和背景音乐分离的步骤，我不清楚是不是bug会报错，如果你也报错的话可以试试这个[在线人声背景音乐分离网站](https://vocalremover.org/zh/)。按着视频讲解走就好
<hr>
<h1>我有一定代码知识，我会用git，我会用github</h1>
直接克隆项目地址：
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">git clone https://github.com/RVC-Boss/GPT-SoVITS.git</span><br></pre></td></tr></table></figure>
<hr>
<p>创建环境</p>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br></pre></td><td class="code"><pre><span class="line">conda create -n gpt-sovits python=3.9</span><br><span class="line">conda activate gpt-sovits</span><br><span class="line">pip install -r requirements.txt</span><br><span class="line">conda install ffmpeg</span><br></pre></td></tr></table></figure>
<p>下载以下两个文件到 GPT-SoVITS 项目根目录</p>
<p><span class="exturl" data-url="aHR0cHM6Ly9odWdnaW5nZmFjZS5jby9sajE5OTUvVm9pY2VDb252ZXJzaW9uV2ViVUkvYmxvYi9tYWluL2ZmbXBlZy5leGU=">https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffmpeg.exe</span></p>
<p><span class="exturl" data-url="aHR0cHM6Ly9odWdnaW5nZmFjZS5jby9sajE5OTUvVm9pY2VDb252ZXJzaW9uV2ViVUkvYmxvYi9tYWluL2ZmcHJvYmUuZXhl">https://huggingface.co/lj1995/VoiceConversionWebUI/blob/main/ffprobe.exe</span></p>
<hr>
<p>下载模型</p>
<p>在 GPT_SoVITS\pretrained_models 打开终端输入</p>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">git clone https://huggingface.co/lj1995/GPT-SoVITS</span><br></pre></td></tr></table></figure>
<hr>
<p>因为 huggingface 是国外的，所以可能会克隆失败，那么我们换用国内的镜像</p>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line">git lfs install</span><br><span class="line">git clone https://www.modelscope.cn/models/AI-ModelScope/GPT-SoVITS</span><br></pre></td></tr></table></figure>
<hr>
<p>下载完模型后，将模型文件拷到 GPT_SoVITS\pretrained_models 目录下。<br>
接着到 modelscope 下载以下模型</p>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br></pre></td><td class="code"><pre><span class="line">git clone https://www.modelscope.cn/iic/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch.git</span><br><span class="line">​</span><br><span class="line">git clone https://www.modelscope.cn/iic/speech_fsmn_vad_zh-cn-16k-common-pytorch.git</span><br><span class="line">​</span><br><span class="line">git clone https://www.modelscope.cn/iic/punc_ct-transformer_zh-cn-common-vocab272727-pytorch.git</span><br></pre></td></tr></table></figure>
<hr>
<p>将以上模型文件放到 tools/damo_asr/models 目录下。</p>
<p>如果训练的音频数据有杂音的话，还需要下载 UVR5 模型对音频先进行去噪处理，放到 tools/uvr5/uvr5_weights 目录下</p>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">git clone https://huggingface.co/lj1995/VoiceConversionWebUI</span><br></pre></td></tr></table></figure>
<p>配置好环境和模型后，在终端输入</p>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">python webui.py</span><br></pre></td></tr></table></figure>
<p>关于报错，如果是 “AssertionError: Torch not compiled with CUDA enabled”，说明装的 Torch 不是 CUDA 版本的，需要重装对应的 CUDA 版本的 pytorch。</p>
<p>如果在离线批量 ASR 时报错 “KeyError: ‘funasr-pipeline is not in the pipelines registry group auto-speech-recognition. Please make sure the correct version of ModelScope library is used.’”，<br>
改 “tools\damo_asr\<span class="exturl" data-url="aHR0cDovL2NtZC1hc3IucHk=">cmd-asr.py</span>” 的代码：</p>
<figure class="highlight plaintext"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br></pre></td><td class="code"><pre><span class="line">path_asr=&#x27;tools/damo_asr/models/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch&#x27;</span><br><span class="line">path_vad=&#x27;tools/damo_asr/models/speech_fsmn_vad_zh-cn-16k-common-pytorch&#x27;</span><br><span class="line">path_punc=&#x27;tools/damo_asr/models/punc_ct-transformer_zh-cn-common-vocab272727-pytorch&#x27;</span><br><span class="line">path_asr=path_asr if os.path.exists(path_asr)else &quot;damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch&quot;</span><br><span class="line">path_vad=path_vad if os.path.exists(path_vad)else &quot;damo/speech_fsmn_vad_zh-cn-16k-common-pytorch&quot;</span><br><span class="line">path_punc=path_punc if os.path.exists(path_punc)else &quot;damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch&quot;</span><br><span class="line">model = AutoModel(model=path_asr,</span><br><span class="line">                  vad_model=path_vad,</span><br><span class="line">                  punc_model=path_punc,</span><br><span class="line">                  #spk_model=&quot;damo/speech_campplus_sv_zh-cn_16k-common&quot;,</span><br><span class="line">                  #spk_model_revision=&quot;v2.0.0&quot;</span><br><span class="line">                  )</span><br><span class="line">opt=[]</span><br><span class="line">for name in os.listdir(dir):</span><br><span class="line">    try:</span><br><span class="line">        text = model.generate(input=&quot;%s/%s&quot;%(dir,name),</span><br><span class="line">                     batch_size_s=300, </span><br><span class="line">                     hotword=&#x27;魔搭&#x27;)</span><br><span class="line">        print(f&quot;asr text:&#123;text&#125;&quot;)</span><br><span class="line">        opt.append(&quot;%s/%s|%s|ZH|%s&quot;%(dir,name,opt_name,text))</span><br><span class="line">    except:</span><br><span class="line">        print(traceback.format_exc())</span><br><span class="line">...</span><br></pre></td></tr></table></figure>
<p>接下来和整合包用法一模一样了（累死我了</p>
<hr>
<h1 id="我的显卡太垃圾了我想云端训练怎么办"><a class="markdownIt-Anchor" href="#我的显卡太垃圾了我想云端训练怎么办">#</a> 我的显卡太垃圾了，我想云端训练怎么办？</h1>
<p><span class="exturl" data-url="aHR0cHM6Ly93d3cuYmlsaWJpbGkuY29tL3ZpZGVvL0JWMXNnNHkxMjdHRC8/c3BtX2lkX2Zyb209MzMzLjMzNy5zZWFyY2gtY2FyZC5hbGwuY2xpY2smYW1wO3ZkX3NvdXJjZT04ZGE3M2RhODhjYzhhZWE5MzZkNmNhZDhmMDBhNDQyZA==">参考视频</span><br>
给你们两个镜像：<span class="exturl" data-url="aHR0cHM6Ly93d3cuY29kZXdpdGhncHUuY29tL2kvUlZDLUJvc3MvR1BULVNvVklUUy9HUFQtU29WSVRT">镜像一</span><br>
<span class="exturl" data-url="aHR0cHM6Ly93d3cuY29kZXdpdGhncHUuY29tL2kvUlZDLUJvc3MvR1BULVNvVklUUy9HUFQtU29WSVRTLU9mZmljaWFs">镜像二</span></p>
<hr>
<h1 id="我是linux系统用户或者macos用户想要本地训练"><a class="markdownIt-Anchor" href="#我是linux系统用户或者macos用户想要本地训练">#</a> 我是 linux 系统用户或者 macOS 用户，想要本地训练</h1>
<p>参考<span class="exturl" data-url="aHR0cHM6Ly9naXRodWIuY29tL1JWQy1Cb3NzL0dQVC1Tb1ZJVFMvYmxvYi9tYWluL2RvY3MvY24vUkVBRE1FLm1k">官方文档</span>，在 CSDN 逛一逛、知乎逛一逛，b 站逛一逛，写教程的人一大堆。</p>
<hr>
<h1 id="我不管我就想白嫖直接玩"><a class="markdownIt-Anchor" href="#我不管我就想白嫖直接玩">#</a> 我不管，我就想白嫖，直接玩</h1>
<p>拿走不谢：</p>
<p><span class="exturl" data-url="aHR0cHM6Ly93d3cubW9kZWxzY29wZS5jbi9zdHVkaW9zL3h6am9zaC9CZXJ0LVZJVFMyL3N1bW1hcnk=">https://www.modelscope.cn/studios/xzjosh/Bert-VITS2/summary</span></p>
<p><span class="exturl" data-url="aHR0cHM6Ly93d3cubW9kZWxzY29wZS5jbi9zdHVkaW9zL3h6am9zaC9HUFQtU29WSVRTL3N1bW1hcnk=">https://www.modelscope.cn/studios/xzjosh/GPT-SoVITS/summary</span></p>
<hr>
<p>训练出的所有的模型请在法律范围内使用。花儿不哭大佬在视频结尾说的一番话，很耐人寻味。思考这种技术，如果落在某讯某飞手里，我们平常人估计很难接触这项技术，使用的话估计也是收费使用的。而开源项目则让这些技术更能服务于大家，而不是掌握在 “少数人手里”—— 开源项目也可以做得很好。背后咬牙切齿的，就是那批赚不到钱、割不到韭菜的人了。</p>

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